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It is a JavaScript library for manipulating documents based on data. Emphasises on web standards gives you the full capabilities of modern browsers without tying yourself to a proprietary framework. | Besides its obvious scientific uses, NumPy can also be used as an efficient multi-dimensional container of generic data. Arbitrary data-types can be defined. This allows NumPy to seamlessly and speedily integrate with a wide variety of databases. | Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more. |
Declarative Approach for Individual Nodes Manipulation;
Functions Factory;
Web Standards;
Built-in ELement Inspector to Debug;
Uses SVG, Canvas, and HTML;
Data-driven approach to DOM Manipulation;
Voronoi Diagrams;
Maps and topo. | Powerful n-dimensional arrays;
Numerical computing tools;
Interoperable;
Performant;
Easy to use | Easy handling of missing data (represented as NaN) in floating point as well as non-floating point data;Size mutability: columns can be inserted and deleted from DataFrame and higher dimensional objects;Automatic and explicit data alignment: objects can be explicitly aligned to a set of labels, or the user can simply ignore the labels and let Series, DataFrame, etc. automatically align the data for you in computations;Powerful, flexible group by functionality to perform split-apply-combine operations on data sets, for both aggregating and transforming data;Make it easy to convert ragged, differently-indexed data in other Python and NumPy data structures into DataFrame objects;Intelligent label-based slicing, fancy indexing, and subsetting of large data sets;Intuitive merging and joining data sets;Flexible reshaping and pivoting of data sets;Hierarchical labeling of axes (possible to have multiple labels per tick);Robust IO tools for loading data from flat files (CSV and delimited), Excel files, databases, and saving/loading data from the ultrafast HDF5 format;Time series-specific functionality: date range generation and frequency conversion, moving window statistics, moving window linear regressions, date shifting and lagging, etc. |
Statistics | ||
GitHub Stars 111.7K | GitHub Stars 30.7K | GitHub Stars - |
GitHub Forks 22.9K | GitHub Forks 11.7K | GitHub Forks - |
Stacks 2.0K | Stacks 4.3K | Stacks 2.1K |
Followers 1.7K | Followers 799 | Followers 1.3K |
Votes 653 | Votes 15 | Votes 23 |
Pros & Cons | ||
Pros
Cons
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Integrations | ||
Highcharts currently supports line, spline, area, areaspline, column, bar, pie, scatter, angular gauges, arearange, areasplinerange, columnrange, bubble, box plot, error bars, funnel, waterfall and polar chart types.
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